Societies have increasingly influenced the frequency and severity of hydrological drought over the past centuries by: i) building dams and reservoirs to secure water supply; ii) diverting water flows to supply cities, industries and agriculture; and iii) changing river basin characteristics through deforestation, urbanization and drainage of wetlands. While societies influence hydrological droughts, drought occurrences (and risks) influence societies. Adaptive responses include migration from drought-affected areas or changes in water allocation and governance. In this talk, I present case studies, global analyses and models to show how these sociohydrological feedbacks can generate legacy risks or social inequalities and thus challenge the development of sustainable policies of disaster risk reduction and water management.

How to cite: Di Baldassarre, G.: Droughts in a human-dominated world: Feedbacks, legacies and inequalities, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4936, https://doi.org/10.5194/egusphere-egu23-4936, 2023.

Drought affects almost every aspect of the environment and society. However, specific sectoral drought impact and risk assessments are often excluded from loss estimates because they are difficult to quantify and/or model. Effectively assessing and managing drought risk requires a multi-scale and multi-sectoral approach to understand the different dimensions of drought. 

The European Drought Observatory for Resilience and Adaptation (EDORA) project addresses the study of drought risk in a multi-system perspective in the European Union. The sectors and systems included in the assessment are agriculture, energy production, water supply, water transport and ecosystems. 

A proper collection and classification of past drought impact data is essential for risk assessment. To this end, we are developing a database of recorded impacts for each system, which can be fed by semi-automated media monitoring, official reports and manual data entries from potential observers. The collection and systematisation of sector specific impacts of drought aims at filling an important gap at the European scale.

Drought risk is assessed in two complementary ways. Risk drivers, root causes of risk and cascading effects are identified and mapped through system-specific impact chains informed by a systematic literature review and expert consultation (including validation workshops). An integrated, cross-system model unveils the interconnections and complexity of drought risk. Also, a modelling tool to quantitatively assess drought risk  was developed for different systems and different regions using machine learning techniques. This data-driven technique uncovers the vulnerability-specific interactions between hazard and impact under present and projected climate conditions. The outcomes of the risk assessments are collected into an atlas showing European multisectoral drought risk at subnational level.

How to cite: Rossi, L., Bláhová, M., Blauhut, V., De Moel, H., Cotti, D., Hagenlocher, M., Kohn, I., Van Loon, A., Maetens, W., Masante, D., Rudari, R., Sabino Siemons, A.-S., Stahl, K., Stephan, R., Szillat, K., Toreti, A., Wens, M., and Naumann, G.: The EDORA project: Towards a multi-sectoral drought risk assessment in Europe, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5948, https://doi.org/10.5194/egusphere-egu23-5948, 2023.

The impacts of drought events can be diverse, far-reaching and encompass multiple sectors and systems. This became particularly evident in recent droughts in Europe (e.g. 2018 and 2022), when, together with extensive damages to agriculture across the whole continent, severe impacts on public water supply, energy production and riverine transportation were also registered. However, while the scientific community has called for the study of these events in their multi-sectoral complexity, research on drought risk and impacts still tends to be conducted in sectoral and disciplinary silos, with different conceptualizations, terminology and methodologies evolving in relative isolation. In order to assess the state of multi-sectoral drought risk research in the European Union, we have completed a systematic literature review (n=168) aimed at understanding how different sectors and systems are represented in drought impacts and risk assessment research in the 27 countries of the European Union (EU27). The analysis focused on peer-reviewed publications and conference proceedings from 2000 to 2022, sourced through the Scopus database, and returned a research landscape where agricultural applications are predominant across the period considered, but in which the representation of other sectors and systems (e.g. energy, ecosystems) is steadily increasing throughout the years. However, only a minority of the studies tackle more than one sector or system (e.g. agriculture and ecosystems), and in most cases the multi-sectoral perspective is not accompanied by a fully integrated assessment of risk in its hazard, exposure and vulnerability components. Another trend of interest is the progressive, albeit still limited, increase in the representation of different geographical clusters among the studies analysed: in particular, while Southern European countries (e.g. Spain, Italy, Portugal) lead in number of case studies, applications to Western European countries (e.g. Germany, France, Austria) have become more frequent. These results can be interpreted as a general improvement towards a more unified understanding and characterization of drought events, but also point at a still high compartmentalization across sectoral fields. Because of the complexity of droughts, this persisting separation may hinder progress towards a common conceptualization of drought events as systemic and multi-sectoral events with multiple direct, indirect and cascading impacts. In particular, a stronger focus on multi-sectoral risk analysis could provide actionable information to support the identification of solutions capable of tackling multiple issues, thus expanding the policy space into which drought risk management can operate.

How to cite: Cotti, D., Sabino Siemons, A.-S., Naumann, G., Wens, M., de Moel, H., Blauhut, V., Stahl, K., Rossi, L., Maetens, W., Toreti, A., and Hagenlocher, M.: Beyond agriculture? A review of cross-sectoral drought risk and impacts research in Europe over the past two decades, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4659, https://doi.org/10.5194/egusphere-egu23-4659, 2023.

Landslides and floods in Italy are the most frequent and diffuse natural hazards causing fatalities and damages to urban areas. Traditional methods as photo-interpretation, remote sensing or retrieval data from technical reports are the most common to set up event inventories. These systems rarely rely on automated or real-time updates. The retrieval of data, using specific data mining algorithms, from newspapers allows continuous feedback from real world and can further extend the exploitable data. Exploiting the data from mass media allows to get information about disaster situations with a relatively high temporal and spatial resolution to map natural hazards across various locations. Several techniques have been developed to mine data for different natural hazard, but rarely applied about landslide and flood news. The algorithm Semantic Engine to Classification and Geotagging News (SECaGN), based on a semantic engine, automatically retrieves information from online newspaper. 184.322 newspaper articles have been harvested from 2010 to 2019, referred to 32.525 landslide news and to 34.560 floods news in Italy. In this work, the data harvested by SECaGN underwent to a manual classification based on news relevance, localization accuracy and time of publication. Most of the news referred to recent events or are generically referred to landslide or floods (remediation work, hazard scenarios) and only a minimum part it was made up by wrong news. This classification allowed to identify the “true news” and to reject the data not appropriate, reducing the uncertainties.

The harvested data have been used to identify the media impact of the events (both landslides or floods), their temporal distribution and those areas where more events happened, allowing a fast hazard estimation of the Country.

The retrieved news data have been then compared with traditional sensors (e.g. rain gauges) and official reports about victims, damages, funds for soil protection and risk maps. Results did not show any clear correlation between the distribution of news and the other parameters, but it resulted that the regions that experienced a relevant number of events recorded lower funds for soil protection and vice versa.

In conclusion, this work allowed to demonstrate the possibility of using automatically retrieved data from newspaper to create a reliable landslide (and flood) inventory, to be used as a proxy for hazard assessment over wide areas and to investigate the distribution of the phenomena and their correlation with other parameters, providing a powerful tool for a rapid hazard assessment in support of public authorities and decision makers.

How to cite: Rosi, A., Franceschini, R., Casagli, N., and Catani, F.: Using automated web data mining for natural hazard assessment, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11984, https://doi.org/10.5194/egusphere-egu23-11984, 2023.

Keywords: Hydrological drought; inland water transport; sensitivity; local communities; climate extremes; climate change

The Amazon River Basin has long been under threat due to climate change. Hydroclimatic records show an increase in both the duration and intensity of recent droughts (e.g., 2005 and 2010) and projections indicate a higher frequency of weather extremes such as droughts and floods in the future. Droughts change river conditions, hence impacting navigation via small and mid-size vessels. Impacts include the total or partial isolation of entire rural communities for weeks or months. With this work we aim to partially answer the following research questions: how have hydrological droughts affected inland water transport in the Amazon basin in recent decades? What were the impacts on local communities associated with constrained accessibility in the region? For that, we used a collection of articles for the period of 2000-2020 from digital media outlets, that is: magazines, newspapers, and other news sources that regularly public their content on the web. The digital media data collection was performed using Google Search engine. To collect the results, we employed the software platform Apify. We set the scraper to return search results for the queries “Amazon”, “drought”, “navigability”; and “Amazon”, “drought”, “isolated” (in Portuguese). News collected from digital media outlets were listed in a spreadsheet and manually processed. We adopted a sequency of exclusion criteria to filter results and produced a table of results with each statement, that is, a text extract from the media items. One digital media news piece can have more than one statement, and whenever that was the case, they were treated separately. We adopted a categorization scheme based on the economic activities/sectors affected by the droughts.

After applying exclusion criteria, the digital media database returned 145 unique entries of statements reporting effects of droughts and/or direct impact on communities from a total of 71 digital media items. Among the 145 unique entries, 119 statements reported impacts of droughts on the lives of local communities. The years of 2005, 2009-2010, 2015-2016 were the most expressive in terms of the number of media pieces reporting effects of droughts according to our analysis. However, localized drier conditions were also registered via media outlets in other years such as 2013, 2018, 2019 and 2020. October was the month with the highest number of news pieces reporting droughts (n = 19), followed by September (n = 15), and August (n = 11). Inland water transport became deeply affected, as reflected by the 97 statements (66.9%). In total, there were 31 statements (21.4%) mentioning impacts on the food supply chain, including wholesale food trade, food retail, grain trade. Logistic issues due to low water levels increased food prices. Impacts on fuel supply were mentioned in 21 statements (14.5%), including impacts on wholesale trade and automotive fuel retail market. Electric power generation and/or distribution were mentioned 6 times in the statements. Due to isolation of communities, many services became affected, such as medical care, access to schools, leisure activities, post service, immunization and pest control.

How to cite: Santos De Lima, L., Teixeira Paradela Cunha, E. L., Dório Anastácio, P. R., Resende Menezes, M. S., Pires Pereira, A. C., de Paula Kolanski, M. M., and Nunes Macedo, M.: Drought effects on inland water transport and impacts on local communities of the Amazon Basin, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-17566, https://doi.org/10.5194/egusphere-egu23-17566, 2023.

Water allocation during droughts is a challenge for policymakers, often addressed through participatory approaches. The implications of this governance mode are understudied as long-term records of the decision-making processes are often unavailable. We use natural language processing (NLP) and network analysis to extract information on water allocation decisions and climate-related issues from meeting minutes of river basin stakeholders. To test this approach, we considered the minutes of 1100 meetings held between 1997 and 2021 in the twelve basin committees of Ceará, Brazil. This region has a long history of droughts, which have strongly influenced water policies and politics. The river basin committee is currently composed of representatives of governmental and non-governmental institutions and deliberates on the water management process. To identify conflicts and relevant issues discussed during the meetings, we created a topic modeling approach consisting of: (1) sentence embedding using SBERT, (2) dimensionality reduction using UMAP, and (3) sentence clustering using K-means. Based on this, we calculated the topic frequency in each committee over time and normalized it by the number of documents registered each year. We also detected the topics mentioned in the same document to build network graphs of co-occurring topics. By using named entity recognition and dependency parsing, we identified the main actors involved during these meetings. Findings indicate that the most common topics were related to 'organic farming', 'fish mortality in reservoirs' and 'structural problems in water infrastructure'. The enhancement of water use monitoring - to identify potential water right violations - seems to be the preferred strategy to cope with droughts. During droughts, stakeholders appear to be more concerned about urban water supply than agriculture demand. We use historical data on water permit granting and water use charging to validate this finding. We also see an increase in climate-informed decisions over time, which became more frequent as new droughts affected the region. In summary, the proposed approach allows exploiting existing text data in order to identify the spatio-temporal patterns of topics related to water allocation. These data are often underexplored due to difficulties in analysing large amounts of text using conventional tools. Hence, text analysis offer exciting new opportunities for research in the field of water management.

How to cite: Nunes Carvalho, T. M., de Souza Filho, F. D. A., and Madruga de Brito, M.: Water management assessment with text mining, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8349, https://doi.org/10.5194/egusphere-egu23-8349, 2023.

Water conflicts generally stem from an imbalance between water demand and availability; as such, they are often studied as a result of meteorological droughts – that is, a lack of precipitation or streamflow. By shifting water availability from wet winters to dry summers, when demand peaks, we hypothesized that snow water resources represent a crucial precursor of this imbalance, and thus play an important, but unexplored role in escalating drought-related water crises and conflict. To shed light on the nexus between snow droughts and increased water challenges, we draw lessons from the extraordinarily warm, dry, and prolonged 2021-2022 snow drought in the Italian Alps, from the consequent spring-to-summer water deficit, and from the relative seeds of conflict. To this end, we compared the spatial distribution of snow water resources deficit with the distribution and type of municipal mandatory water restrictions, under the assumption that the former are proxies of a future deficit in availability, while the latter are proxies of an imbalance between this availability and needs. We found initial evidence that the location and magnitude of the deficit in snow water resources observed across the Italian Alps in winter 2022 (-60% or more at peak accumulation) did result in seeds of institutional conflicts later in spring and summer. These findings can aid institutions and policymakers in understanding the mechanisms behind emerging water conflicts and their implications, and so design ad-hoc water policies, especially in a warming climate.

How to cite: Munerol, F., Avanzi, F., Morando, M., Altamura, M., Gabellani, S., Galvagno, M., Cremonese, E., and Ferraris, L.: Snow droughts as a precursor of water conflicts, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5634, https://doi.org/10.5194/egusphere-egu23-5634, 2023.

For several seismic-prone countries, current earthquake insurance solutions cover only a small part of the economic loss. Innovative insurance products like parametric insurance are emerging for which the compensation is calculated upon a trigger instead of a claim amount, covering more people but with drawbacks due to probable difference between the insurance compensation and the actual loss. In this paper, new insurance model is proposed, covering earthquake risk for residential houses. Its main characteristics are: (1) the compensation is to rebuild the insured house, instead of paying a financial amount; (2) the model leverages both on long-term financial investment and seismic retrofitting of the insured buildings to make the premium amount affordable; and (3) joint participation of the public authorities and the homebuilder companies in this insurance model are expected since the first ones are the key player in risk prevention plans and the second ones are the beneficiary of this new market (incentivizing repairs/reconstruction and retrofitting works). Results show that in most cases the price (i.e. premium amount and retrofitting costs) for this earthquake insurance model is lower than the premium amount considering the traditional earthquake insurance. For the optimal deductible amount, the decrease can even be three times lower than for classical model, by assuming a contribution from both the public authorities and the homebuilder companies. Such a decrease could raise the rate of California homeowners insured against earthquake risk from 15% up to 50%.

How to cite: pothon, A.: A long-term property earthquake insurance: illustration with the housing sector in California, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13009, https://doi.org/10.5194/egusphere-egu23-13009, 2023.

Sinkholes that occur in settled carbonate lands can be a critical source of risk for human properties and activities since they can abruptly produce serious damage to property and people in densely populated flat areas. This work presents a sinkhole susceptibility and risk assessment mapping in Guidonia-Bagni di Tivoli plain (Central Italy), which is a carbonate sinkhole-prone study area where sudden occurrences of sinkholes have happened in past and recent times. We consider a point-like sinkhole inventory and a series of environmental sinkhole-controlling factors on the study area, related to its geo-litho-hydrological asset, i.e. travertine thickness, and to its terrain deformational scenario, i.e. ground motion rates derived from InSAR COSMO-SkyMed imagery. A sinkhole susceptibility map was generated by means of maximum entropy algorithm  - MaxEnt model – and it was then combined with data on vulnerability and elements-at-risk economic exposure derived from cadastral inventories and market and income values, in order to provide a final sinkhole risk map of the Guidonia-Bagni di Tivoli area. The results show that areas at higher risk covers about 2% of the total study area and primarily relies on the zoning of the main urban fabric. In particular, it is worth to highlight that 5% of the whole road-network pavement and 27% of all the residential buildings fall into higher risk classes. Outcomes of this work reveal the potential of MaxEnt model to assess sinkhole susceptibility for predicting sinkhole areas, either provide a sinkhole risk map as a useful tool for geohazard risk and urban planning management strategies.

How to cite: Bianchini, S., Confuorto, P., Intrieri, E., Sbarra, P., Di Martire, D., Calcaterra, D., and Fanti, R.: Sinkhole risk assessment by using machine learning model: the case study of Guidonia-Bagni di Tivoli plain (Rome), Italy, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11993, https://doi.org/10.5194/egusphere-egu23-11993, 2023.

Hail is a severe meteorological hazard that can cause significant damage to both buildings and cars. Here, we present the first-ever open-source risk model for hail damages, provided within the CLIMADA framework. The availability of high-resolution radar-based hail intensity measures and detailed damage and exposure data from local insurance companies in Switzerland allows for a spatially explicit calibration of vulnerability functions for buildings and cars. The model is able to provide climatological evaluations of hail risk and real-time hail damage estimates based on any user-provided exposure data. Furthermore, combined with crowd-sourced hail reports, the detailed damage data allows for an evaluation and uncertainty quantification of different radar-based hail intensity measures. In a second step, the model will be expanded to use high-resolution convection-resolving simulations with the hail growth module HAILCAST as hazard variable. This enables the assessment of hail risk under climate change, as well as the prototyping of an impact-based warning system based on ensemble weather forecasts. The open-source nature of the model allows for easy access and modification by any interested party, including insurance companies, government agencies, and the general public, making it a valuable tool for assessing hail risk and implementing effective mitigation strategies.

How to cite: Schmid, T. and Bresch, D. N.: Open-source Risk Model for Hail Damages to Buildings and Cars: From Climatological Evaluation to Impact-based Warnings, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3264, https://doi.org/10.5194/egusphere-egu23-3264, 2023.